Liu Zhixin, Sun Chaochao, Qu Jili, Mokhov Alexander
School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China.
School of Civil Engineering, Kashi University, Kashi 844000, China.
Materials (Basel). 2025 Mar 4;18(5):1151. doi: 10.3390/ma18051151.
This paper investigates the effect of fiber-reinforced composites (FRPs) on the mechanical properties of concrete under ambient conditions. It begins with an examination of the various types of FRP and their advantages, followed by a review of isostructural models for passively restrained concrete under ambient conditions. These models are categorized into two main groups: those assuming constant confining stresses and those that incorporate stress constraints related to the loading history. Recent studies have highlighted the significant role of stress paths in determining the stress-strain behavior of concrete. Traditional methods for predicting the FRP-constrained concrete reinforcement bond at room temperature are increasingly being replaced by machine learning techniques, such as Artificial Neural Networks (ANNs) and Genetic Expression Programming (GEP), which offer superior accuracy in predicting the FRP-constrained concrete bond strength and the compressive properties of FRP-confined concrete columns. In particular, experimental results show that the compressive strength of FRP-confined concrete columns can increase by up to 30-250%. This review offers valuable insights into the effects of FRP on concrete and contributes to the advancement of engineering design practices.
本文研究了纤维增强复合材料(FRP)在环境条件下对混凝土力学性能的影响。文章首先考察了各种类型的FRP及其优点,接着回顾了环境条件下被动约束混凝土的等结构模型。这些模型主要分为两类:一类假设围压恒定,另一类考虑与加载历史相关的应力约束。近期研究强调了应力路径在确定混凝土应力-应变行为方面的重要作用。传统的预测室温下FRP约束混凝土增强粘结力的方法正越来越多地被机器学习技术所取代,如人工神经网络(ANN)和基因表达式编程(GEP),它们在预测FRP约束混凝土粘结强度和FRP约束混凝土柱的抗压性能方面具有更高的准确性。特别是,实验结果表明,FRP约束混凝土柱的抗压强度可提高30%至250%。本综述为FRP对混凝土的影响提供了有价值的见解,并有助于工程设计实践的进步。